Environmental trade-offs of direct air capture technologies in climate change mitigation toward 2100

Direct air capture (DAC) is critical for achieving stringent climate targets, yet the environmental implications of its large-scale deployment have not been evaluated in this context. Performing a prospective life cycle assessment for two promising technologies in a series of climate change mitigation scenarios, we find that electricity sector decarbonization and DAC technology improvements are both indispensable to avoid environmental problem-shifting. Decarbonizing the electricity sector improves the sequestration efficiency, but also increases the terrestrial ecotoxicity and metal depletion levels per tonne of CO2 sequestered via DAC. These increases can be reduced by improvements in DAC material and energy use efficiencies. DAC exhibits regional environmental impact variations, highlighting the importance of smart siting related to energy system planning and integration. DAC deployment aids the achievement of long-term climate targets, its environmental and climate performance however depend on sectoral mitigation actions, and thus should not suggest a relaxation of sectoral decarbonization targets.

. Impact categories include (a) climate change impact, (b) human toxicity impact, (c) freshwater eutrophication impact, (d) freshwater ecotoxicity impact, (e) terrestrial acidification impact, (f) terrestrial ecotoxicity impact, (g) metal depletion, (h) water depletion. Under each impact category, the results include four DACCS and heat sources combinations (Solvent-based DACCS that uses biomethane or natural gas as a heat source. Sorbent-based DACCS that uses biomethane or heat pump as a heat source). The colors of the stacked bar represent different life cycle stages. Each year corresponds to two bars representing the results of no technology learning ("NL", on the left) and with technology learning ("L", on the right).

Supplementary Note 1: Life cycle inventory of two DACCS technologies
In this section, we provide the life cycle inventory (LCI) data of both solvent-and sorbent-based direct air capture (DAC) systems and subsequent compression and storage system. In the literature, some life cycle inventory (LCI) data of construction and operation of solvent-based DAC systems are missing, so we estimate some of the missing data based on engineering analysis of the material flow, equipment heuristics.

Material requirements and assumptions of solvent-based DAC
In this study, solvent-based DAC uses aqueous potassium hydroxide (KOH) solutions to capture atmospheric CO2. The plant has an annual capacity of capturing 1 million metric tonnes (Mt) CO2, with a lifetime of 20 years. The plant has four major components (contactor, pallet reactor, calciner, and slaker) and some auxiliary equipment. The material requirement data for constructing the air contactor of a solvent-based DAC plant are provided de Jong et al. 1 , so these data are directly used as LCI of air contactor in this study. As for other components, the LCI data are missing in the literature, so their material requirements data were determined by sizing the equipment in accordance with the material flows in Keith et al (2018) 2 , engineering equipment heuristics, sizing approximations based on existing images and industry standards, and existing patents held by Carbon Engineering, which are described below.
Material requirements: Pellet reactor The pellet reactor used by Carbon Engineering (CE) is a customized version of a wastewater treatment reactor designed by Royal HaskoningDHV, called the Crystalactor® 2 . From the renderings provided in Keith et al (2018), it was estimated that a 1 MtCO2/year plant requires 48 pellet reactors. Each reactor shell is a stainless-steel cylinder with a height of 12 m and a diameter of 1.2 m. The actual shell may be more complex, but specific data could not be found. The wall thickness is assumed to be 0.022 m. This thickness comes from a safety factor of 3.5 given for a vertical vessel under pressure and with a diameter about 1 m, which account for potential corrosion risks 3 . The reactor shell has a 60-degree conical base with a diameter of 1.2 m. From this, the sidewall height of the base was calculated to be 3.6 m. The base thickness was assumed to be, again, 0.022 m due to the given conditions. The reactor lid was assumed to be a flat cap with a diameter of 1.2 m and a thickness of 0.022 m. Extra material required for a more complex lid was considered negligible. For the 48 vessel shells, bases, and lids, this results in a total stainless-steel requirement of 454 t/plant. Additional material required for automatic addition of seeds, washing and drying of seeds, and processing of fines were included in the Material requirements: Other equipment.

Material requirements: Calciner
The process proposed in Keith et al (2018). employs an oxy-fired fluidized bed calciner to produce calcium oxide (CaO) from calcium carbonate (CaCO3). The calcination step can be broken up into three steps: preheat, calcination and cooling: The preheat step includes two cyclone heat exchangers (preheat 1 and preheat 2), that heat up solid stream (mostly CaCO3) up to about 650°C. Since the material flow to the calciner is greater than 2,500 t/day, we assume that these cyclones are built as twin systems for a total of four cyclone preheaters. The diameters of the preheat 1 and preheat 2 are estimated at 8.1 m and 7.6 m, respectively (scaled based on the increased diameter and throughput presented in a previous study 4 ). Further, the material requirements were determined based on the circumference of the preheat cyclone and materials information from literature 5 . The preheat system also requires additional ducts leading from cyclone to cyclone, a draft fan for each set of cyclone preheaters, or a dip tube to increase material separation efficiency. These material requirements are included in Material requirements: Other equipment.
The calcination step in the Keith et al (2018) is based on fluidized bed calciner reactor, but we estimate the calciner material requirements using a rotary kiln, which is more widely deployed in industries such as cement making and pulp and paper production. While the two calciner configurations are different, the differences are assumed to have negligible effects on the material requirements for the calciner. Most of the material requirements for the calciner are from the metal body (in this case, steel) and the refractory (in this case, red brick refractory or alumina brick refractory). The material requirements for the calciner can be estimated using a cylindrical reactor with single refractory brick lining. The two primary material requirements are steel for the kiln shell and alumina bricks for the working refractory. Assuming the inside of the rotary kiln capable of processing 1,600 t raw material per day is 5.5 m, the working refractory layer is 0.254 m (or 10 inches) and the steel kiln shell is 0.04 m thick, this adds 1,000 t of steel and 2,050 t of red refractory brick for 1 Mt CO2/year facility. These material requirements are then scaled linearly to achieve a throughput 3,960 t/day. Since the rotary kiln configuration is different than the fluidized bed, we then adjust the material requirements linearly using the projected cost. The cost of an oxy-fired rotary calciner is assumed to be $120 million 6 ., where the projected cost for the oxyfired fluidized bed calciner is $44 million from Keith et al (2018). Scaling these values yields material requirements of 910 t steel/plant and 1,856 t refractory/plant. The cooling is a step after the calcination where the produced CaO is sent to an additional cyclone heat exchanger that preheats the incoming oxygen stream. Similar to the preheat, we assume that there are two, identical cyclones necessary on account of the high flow rate. The material requirements for the cyclone are estimated to be identical to cyclone preheat 2 with a radius of 7.6 m.
The complete material requirements for the calciner, broken down into the three sections, is shown in Supplementary Table 1. Two processes occur simultaneously inside of the slaker at 300°C: an exothermic reaction between CaO and water to produce Ca(OH)2 and the heat transfer to solid CaCO3 as a preheat to the calciner system 7 .

Supplementary
The reaction vessel processes the solid CaO stream leaving the oxygen preheat (170 t/hr, 97% CaO, 3% K2CO3), water condensed from the steam turbine (70.2 t/hr), solids from the upstream CaCO3 filter (306 t/hr, 98.2% CaCO3, 1.8% K2CO3) and a recycle steam stream 2 . We assume this vessel is primarily steel (used to form the shell of the reactor) and refractory brick (used as insulation).
The solvent process presented in Keith et al 2 and detailed in Heidel and Rossi 7 uses a novel slaker configuration, mixing both the CaCO3 streams and CaO streams to dry the CaCO3 stream and recycle uncalcined material to the calciner, as well as create Ca(OH)2. On account of the lower temperature requirement (300°C), we assume a refractory thickness of 6 inches (0.1524 m) total 8,9 . We assume that for the two calciners, there will be two slaking units, processing a total of 476 t/hr of solid material and roughly 70.2 t/hr of liquid/gaseous materials with equal distribution 2 .
The outer shell of the slaker is assumed to be 40 mm, consistent with the metal shell thickness used for the calciner. The fluidization velocity is 1 m/s 2 . Assuming that the fluidizing medium is primarily steam, the specific volume of the superheated steam stream can be determined at 300°C and 1 bar (2.6 m 3 /kg) to give a gas volumetric flowrate of 0.46 m 3 /s. Therefore, we assume each slaker is a 0.4 m diameter cylindrical reaction vessel with an attached chamber for a recycle stream that is estimated using a factor 1.5 for the additional steel and refractory requirements based on the relative sizing of the cylindrical vessel to the recycle chamber. Assuming that the solid particle size entering the slacker experiences little to no particle size reduction occurring in the calciner, all particles will be roughly 0.85 mm in diameter when entering the slaker 2 .
For most industrial fluidized beds, the length to diameter ratio lies between 3 and 16 10 and the typical reactor length is between 1 and 10 m 11 . For this analysis, we assume a bed length of 7.6 m (or a L/D ratio of 10). For the refractory thickness of 0.1524 m, the red silica brick requirement per vessel is roughly 9 t/ reactor. For the steel thickness of 40 mm, the steel requirements are roughly 8 t/reactor. The total requirements for capturing 1 MtCO2/year from air is shown in Supplementary Table 2. The steam slaker requires additional equipment, such as a cyclone that separates the outlet gas stream, a baghouse unit, fines filter (separating CaCO3 and Ca(OH)2 post-slaker), heat exchangers and coolers. The material requirements for these smaller unit operations are included in Material requirements: Other equipment.

Material requirements: Other equipment
The material requirements for additional process equipment are assumed to be primarily concrete and steel. These additional units include the fines filter, quicklime mix tank, heat exchanger, and pumps, as well as any additional auxiliary equipment. To estimate the requirement for concrete, we assume 34% of the material costs from Keith et al. (2018) is distributed to concrete which is based on the American Institute of Steel Construction (AISC) construction material cost ratio to estimate the concrete requirements 12 . This is also similar to the methodology used in the Rhodium Group report Capturing New Jobs 13 . We assume a cost of concrete is $61/t 14 , consistent with the commodity price as of 2018. The resulting concrete requirements for the facility are calculated and outlined in Supplementary Table  3. The material requirements associated with piping and instrumentation are primarily steel and aluminum, and we estimate that separately based on a refinery configuration. The material requirements of any subsets (pipe, tubing, valves, fittings, and flanges) of the refinery (at three capacity levels: 10,000, 75,000, and 150,000 barrels/stream day) are provided in the Critical Materials Requirements for Petroleum Refining 15 , then we calculated the steel requirements of the refinery with total capital cost of $6.06 billion (2018$) and a capacity of 50,000 barrel/stream day 16 using the scaling factor shown in Eq. 1 below.

Scale Factor=
Then, we calculate the material requirements associated with piping and instrumentation of the solventbased DAC as proportionate to that of the refinery plant (50,000 barrel/stream day) based on their capital costs (total capital cost are $6.06 billion for the refinery, total capital cost is $1.13 billion for solvent-based DAC 2 , both on 2018$). The material requirements associated with piping and instrumentation are given in Supplementary Table 4. The initial requirements of CaCO3 are required to start up the system. This is calculated using Figure 2 from Keith et al. 2 . The inlet CaCO3 includes the three streams of CaCO3 entering the pellet reactor: (1) CaCO3 Seed (4.5 t/h), (2) CaCO3 Makeup (3.4 t/h) and (3) CaCO3 Seed from Calciner (6.0 t/h). The total startup CaCO3 is 13.9 t/h for the duration of the startup period. The startup period discussed here is for the calcium loop (or calcining loop) and it primarily depends upon the calciner. Here, we assume a startup time of 24 hours to account for transit time through the calciner and associated equipment, which results in an initial CaCO3 requirements to be 330 t. After the initial startup period, the annual make-up CaCO3 is 3500 t/year 17 . Therefore, the annualized CaCO3 consumption is 3,517 t (= 330t/20 + 3,500t).

Chemical Requirements: Potassium Hydroxide (KOH)
The initial KOH requirements are also directly dependent on the startup time of the system. Keith et al. 2 uses a 2 mol/L KOH solution that flows to both the contactor and post-combustion absorber at a flow rate of 35,000 t/hr. This is equivalent to roughly 3,000 t of KOH per hour for the duration of the startup period. We assume the same startup time of 24 hours to startup, including circulation from the contactors to the regeneration facility and the fluid residence time in the pellet reactors. In other words, the startup time accounts for the complete circulation of the fluid through the caustic recovery loop. So, the initial KOH requirement is 72,000 t. Although KOH is recycled through the system, but drift losses leads to an annual make-up KOH of 400 t/year 17 . Therefore, the annualized KOH consumption is 4,000 t (= 72,000t/20 + 400t).
Chemical Requirements: Water The initial water requirements can also be estimated using the 35,000 t/h solvent flow to the contactor 2 , which implies a water usage of roughly 31,000 t/h for the startup period of the contacting loop. With a startup time of 24 hours, the initial water usage is 744,000t. The temperature and relative humidity are used to estimate the water losses using the correlation given in Keith et al. 2 . We assumed a 60% relative humidity and 20°C, which resembles the temperature and humidity near Midland Texas November to March 18 . At these conditions, the evaporative losses are 3.8 t water/t CO2 (430 t water/hour). By assuming a 90% operation capacity of DAC facility (7,884 hour/year), the annual make-up water is 3.4 Mt water/year. Therefore, the annualized water consumption is 3.44 Mt/year (= 0.74 Mt/20 + 3.4 Mt).
The overall material requirements for the construction of a 1 MtCO2/year solvent-based DAC (except for air contactor) and its annualized chemical and water consumption of are summarized in Supplementary  Table 5. The material and energy requirement data are converted to LCI data for solvent-based DAC systems and the subsequent compression and storage system based on 1 functional unit (capturing 1 t CO2), which are summarized in Supplementary Table 6. Two heat supply options (natural gas and biomethane) are considered for solvent-based DAC system, and the inventory data of the heat supply are provided. e ecoinvent 3.6 database does not include LCI data of the "RoW: heat production, biomethane, at boiler condensing modulating <100kW" process, but the LCI data of this process is included in the newest version (ecoinvent 3.7). Therefore, we collected the LCI datasets related this process from ecoinvent 3.7 and added them to ecoinvent 3.6 to create an extended ecoinvent 3.6. The data is also summarized in "4_LCI_biomethane_heat.xlsx" excel file in "LCI_data" folder. f End-of-life (EoL) phase includes the treatment of materials used in construction and operation of DAC facility. We assume 85% steel (including low-alloyed and stainless steel, and steel pipe) used in the construction phase is recycled during end-oflife phase, and 90% aluminium used in the construction phase is recycled during end-of-life phase. All other materials (100%) are either incinerated or landfilled. g Unit conversion of concrete from volume to mass by assuming the density of concrete as 2400 kg/m 3 .

Life cycle inventory of sorbent-based DAC
For the sorbent system, the LCI data are collected from the work of Deutz and Bardow based on the Climeworks system 19 . We used the LCI data of the plant with an annual capacity of 100 kt CO2/year and a lifetime of 20 years. The LCI data are summarized in Supplementary Table 7. RoW: treatment of spent anion exchange resin from potable water production, municipal incineration 3 kg Notes: a Two heat supply options (heat pump and biomethane) are considered for sorbent-based DAC system, and the inventory data of the heat supply are provided. The heat pump considered in this study has a coefficient of performance (COP) of 2.5, and it converts electricity into heat, so we use inventory of electricity production to represent the inventory of heat generation from heat pump. Heat requirement of sorbent-based DAC is 5,400 MJ/t CO2 captured. If heat pump with COP of 2.5 is used to provide heat, the electricity consumption is 2,160 MJ/t CO2 captured (600 kWh/t CO2 captured).

Life cycle inventory of amine-based silica
The specific solid sorbent we choose for the sorbent-based DAC is amine-based silica, which can be synthesized by impregnate amines polyethylenimine (PEI) on solid silica gel. The LCI of amine-based silica is collected from literature (taking average between the best-and worst-case) 19 and summarized in Supplementary Table 8 based on the composition that 1 kg amine-based silica requires of 0.64kg silica gel and 0.36 kg PEI 20 (The data is also summarized in "3_LCI_amine_based_sorbent.xlsx" excel file in "LCI_data" folder).

Life cycle inventory of pipeline transport and storage system
Once the captured CO2 is release from the DAC system, we assume the CO2 flow will be compressed through a compressor to 11 MPa and then transported through a pipeline to the storage site. The length of the transport pipeline is assumed to be 50 km. At the storage site, the CO2 will be further compressed to 15 MPa and injected into a geological reservoir through wells with the depth of 3 km each. The LCI data of transport and storage system are collected from a previous study 21 and summarized in Supplementary Table 9.

Supplementary Note 2: Technology learning assumption of solvent-and sorbent-based DAC
Solvent-based DAC approach uses a liquid solvent and high surface area packing material to capture ambient CO2. Current applications require strong bases, such as NaOH and KOH, with uptake of 3.1E-5 mol CO2/cm 2 •second (0.52 mol CO2/minute•m 3 ) 22 . If innovative approaches can increase the uptake rate to 7.0E-5 mol CO2/cm 2 •second (1.18 mol CO2/minute•m 3 ), this would result in a 2.3 times increase in the uptake rate. This could result from an improved packing material that increases the solvent's exposed surface area, or by the development of novel liquid solvents with higher uptake capacities. The increase in uptake translates to a roughly proportional decrease in the bed depth of the contactor and a roughly 56% decrease in the cost of the contactor unit. The decreased bed depth additionally causes a reduction in the system fan power by the same percentage. Then, we also assumed that increased deployment improves the system thermal efficiency, which results in a reduction of system thermal energy demand by 2.4 GJ/tCO2 for a total energy requirement of 6 GJ/tCO2 23  For initial cost of solvent-based DAC, we used the upper bound cost data from the NASEM report, which is $264/tCO2 (capital cost = $151/t CO2, operating cost = $113/t CO2, with a capacity of 1 Mt CO2/year) 24 .
To estimate the how these costs will come down, we applied the 56% decrease to the capital cost of contactor, and we assumed that innovation in other unit operations will result in achievement of the lower bound capital costs as described in the NASEM report. So, we developed the theoretical minimum capital cost at $67/t CO2 (44% of today's capital cost). (A capital recovery factor of 12.4% was used annualize the capital costs of the system). Then, we adopted a learning rate range (1% to 15%) 25 from various existing emerging technologies to project the reduction of capital cost. Under 10% learning rate, the capital cost approximates to the minimum $67/t CO2 when the learning effect is saturated, so the 10% is chosen as the reference learning rate for capital costs of solvent-based DAC. Furthermore, we adopted a range of learning rate (5%-15%) for the capital cost of solvent-based DAC from the literature to reflect uncertainty in the actual learning rate 26 . Similarly, to adjust the operating cost, the fan energy was reduced by 56% and a reduction of 2.4 GJ/tCO2 is applied to the thermal energy demand, which give the minimum operating costs at $56/tCO2 (50% of today's operating cost). As for the learning rate, a few previous studies adopted a conservative assumption by considering a fixed operating cost (no learning) over time 25,26 , so here we assumed an reference learning rate of 2.5% for the operating cost, with a range varying from 0% (no learning) to 5%.
Sorbent-based DAC uses solid sorbents to uptake CO2 in a batch-wise process. The first area for innovation lies within the sorbent itself. Sorbents designed with higher uptake rate and longer lifetimes can reduce the amount of sorbent necessary in the DAC contactors. Since the sorbent makes up roughly 80% of the system's capital cost 27 , this has a huge impact on the process economics. The current uptake observed in commercial sorbents is 2.5 mol CO2/kg over 3,000 s (3.53 mol CO2/minute•m 3 ) 22,24 . Higher capacity sorbents are described to reach an uptake of 3.4 mol CO2/kg over 12 hours in an aminopolymer-impregnated silica sorbent 28 . If future innovation can lead to similar uptakes in 3,000 s, this increases the specific uptake to 4.76 mol CO2/minute•m 3 . Additionally, we assume that the average lifetime will lengthen from 0.5 years to 2 years 24 , which reduces the amount of makeup sorbent by four times the original value. The joint impact of increased uptake and longer sorbent lifetime results in a sorbent cost decrease of roughly 82%, resulting in a 74% decrease in the overall capital costs compared to the middle case NASEM report. The cost per unit sorbent is assumed to remain consistent at $50/kg. Due to the potential reduction of sorbent use described above, we assume the learning rate and the theoretical minimum value of sorbent use will be the same as those applied for capital cost of sorbent DACCS.
The cost data from scenario 4 -High in the same NASEM represent the cost of sorbent-based DAC with the plant capacity 1 Mt CO2/year too. After adjusting the capital cost to represent an economic lifetime of 10 years and a 11.6% discount rate, the total cost is $386/tCO2 (capital cost = $364/t CO2, operating cost = $22/t CO2). In this study, life cycle inventory data we used for sorbent-DAC is based on plant capacity of 0.1 Mt CO2/year, so we further estimated the initial cost of a sorbent-DAC with the capacity of 0.1 Mt CO2/year using the learning curve approach. We assumed the plant with the capacity of 4,000t CO2/year to be $900/t CO2 (by averaging the costs of 4,000t CO2/year sorbent-based plant from multiple sources 25,29 ), and then the cost of a plant with the capacity of 1 Mt CO2/year was assumed to be $386/tCO2. We fitted these data into a regression of one factor learning curve equation, and then we estimated the cost of a sorbent-DAC with the capacity of 0.1 Mt CO2/year to be $550/tCO2 (capital cost = $518/t CO2, operating cost = $32/t CO2), and we use this cost as the initial cost of sorbent-based DAC plant (with the capacity of 0.1 Mt CO2/year).
The aforementioned changes to the sorbent capacity and lifetime coupled to the assumption that other process innovations will shift the capital cost from scenario 4 -High to scenario-2 Low described in the NASEM report result in a reduction of the system's levelized capital costs by 82% ($101/tCO2). For the operating cost, we also shift it from scenario 4 -High to scenario 2 -Low, resulting in a minimum operating cost of $16/tCO2 (50% of initial operating cost). Using similar method for developing the learning rate as described in the solvent-based DAC, we adopted a learning rate range for sorbent-based DAC, which is from 5% to 20%. The higher range is chosen is because, compared to solvent-based DAC which is highly integrated and large-scale, sorbent-based DAC relies on standardized and modular units, which can be mass-produced and deployed, and therefore enables fast iteration and learning 26 . The learning rate chosen to best represent the capital costs of sorbent-based DAC is 15% (as the reference learning rate), and the uncertainty range was set to be 10%-20% 26 . For the operating cost, we used the same learning rate as the solvent-based DAC, with the reference rate being 2.5% and variation range being 0%-5%.
Here, we also assume that the subsequent CO2 transport and storage facilities will follow the same learning rates as the corresponding solvent-and sorbent-based DAC systems. The selected learning rates and theoretical minimum costs of both solvent-and sorbent-based DACCS are summarized in the Supplementary Table 10. Because the effects of technology learning on material and energy use of DACCS are so far missing in the published literature, we assume the changes of material and energy consumption are proportional to the changes of the costs of DACCS technologies. Therefore, we used these learning rates and their theoretical minimum values to estimate the corresponding material and energy uses that are related to these cost metrics. There is no concrete way to imply the learning rate between two points. This approximation has DACCS approaching a theoretical minimum cost at different rates. Future innovation is unpredictable and, therefore, the actual minimum cost may be different from the estimated values.  Table 10). The material and energy use factors are 1 in the starting year (2020), and then factors of the following year are expressed as the ratios relative to those in 2020 as the technology learning starts. By multiplying these material and energy use factors to the actual amount of material and energy uses of DACCS systems in 2020, we can get the dynamic material and energy use data of DACCS, which can be used as LCI data to evaluate the prospective environmental impacts of DACCS with the consideration of technology learning. The results under the columns named by "Reference" were estimated based on the reference learning rates in Supplementary Table 10.

Supplementary
The results under columns named by "Slow" and "Fast" were estimated based on the lower bound (slow) and upper bound (fast) learning rates, respectively, and that is why the results under "Slow" column (representing slow learning) have higher numeric values, while the results under "Fast" column (representing fast learning) have lower numeric values.

Supplementary
Offshore wind power electricity production, wind, 1-3MW turbine, offshore Wave power a electricity production, wave Hydro power electricity production, hydro, reservoir, alpine region, electricity production, hydro, reservoir, non-alpine region, electricity production, hydro, reservoir, tropical region, electricity production, hydro, run-of-river Other renewables (tidal and geothermal power) electricity production, deep geothermal Nuclear electricity production, nuclear, boiling water reactor, electricity production, nuclear, pressure water reactor, heavy water moderated, electricity production, nuclear, pressure water reactor Coal steam turbine electricity production, hard coal, electricity production, lignite, electricity production, peat, electricity production, hard coal, conventional, electricity production, hard coal, supercritical Oil steam turbine electricity production, oil Natural gas open cycle turbine electricity production, natural gas, conventional power plant Biomass steam turbine electricity production, wood, future Integrated gasification combined cycle b Note: a LCI of wave electricity generation is collected based on an attenuator-type floating oscillating body system wave energy converter with a capacity of 750kW 31 . The LCI data is also summarized in "1_LCI_wave_electricity.xlsx" excel file in "LCI_data" folder. b We adopted the LCI of fossil fuel with CCS that is summarized in a previous study 30 . The LCI data is also summarized in "2_LCI_CCS.xlsx" excel file in "LCI_data" folder.